2025 Global AI Job Market: Salaries, Skills, and Trends
Introduction
It's no secret that artificial intelligence is having a massive impact on the world, from LLMs (large language models) like ChatGPT or other deep learning based models such as Google DeepMind's AlphaFold, which predicts protein structures. However, where I want to focus is its impact on the software engineering job market, especially for AI positions. The reasons for focusing here are:
- I personally want to work in this field 😂
- Unfortunately, in my opinion, positions such as frontend developer or mobile devs will be mainly replaced in the future. Especially the more junior positions (which is not too good for me 🤣)
However, no more fear-mongering, as this does allow for a whole host of new opportunities for software developers to get into a new and exciting field that is changing the world. I have been analysing a dataset from
Kaggle that has data on 15,000 job postings. The data includes the normalised salary to USD, experience level (Entry, Mid, Senior, Executive), the skills needed, education level needed for each role, and more.
- Entry Level: 3,718
- Mid-Level: 3,781
- Senior Level: 3,741
- Executive: 3,760
The roles are sourced from major job platforms worldwide including:
- LinkedIn Jobs
- Indeed
- Glassdoor
- AngelList
- Stack Overflow Jobs
- Company career pages
The job postings are taken from January 2024 to April 2025. The most amount of jobs collected in one month is 985 for the month of April 2024 and the minimum amount of jobs is in February 2025 with 840 jobs. The average amount of jobs added each month over the dataset is 937.5.
Lastly, also stated is that all entries are manually verified and standardised
So let's begin!We will start with everyone's favourite subject: 💵💵
The dataset provided pretty evenly distributes the company locations of the job posts (this doesn't mean that you can't work remote), meaning we can get a pretty good insight into how different countries vary in terms of salary, etc. As seen here:
However, something that comes as a surprise to absolutely no one is that if you consider the average salary across all experience levels the average salary by location is not equal.
From this we can see that the top 10 highest paying locations are all economically developed countries. These countries often have higher costs of living and a greater demand for specialised positions, both of which contribute to elevated salaries. This trend also continues when you break down the average salary by experience level:
The same story is told when looking at the country of which the employee resides in. The only difference is that the UK drops down a couple of positions but, with an average salary of over $120,000, I don't think those developers mind too much. It is also worth pointing out that out of the data provided, 71.63% of workers worked at company locations that were in the same country as they reside in, compared to 28.37% who worked for companies located in a foreign nation.
Now, if you're thinking that's nice, but I'm not really in a position to move country, what job in AI should I be looking for? My answer to that would be: Take your pick, all the salaries for the provided positions are one very strong, and two pretty similar, with not much variation.
As you can see the difference between the salaries of somebody in an entry-level position is drastically different to those in higher positions. This is to be expected and not necessarily a bad thing, especially when the mean salary for entry-level positions is ~$63,000.
The general public, when thinking of tech companies, probably thinks of MAANG (Meta (formerly Facebook), Amazon, Apple, Netflix, and Google), mainly as these are the tech companies they interact with the most they search through Facebook or Netflix on their Apple iPhone or they search for Amazon on Google, or they use Meta's VR Quest headset. However, yes, these companies do pay very well and carry a lot of prestige it's not the be-all and end-all that you may think. Most companies, large or small, pay very well for AI positions, according to this data, as you can see below.
Since the pandemic, remote work has become more common, so it's worth checking out if that has any correlation with salary. In the graph below, you can see that whether the position is either remote, hybrid or completely in the office, according to this data, it plays no role on your salary. The main correlation is caused by how many years of experience you have.
In summary, the data highlights a strong correlation between geographical location, experience level, and salary. Economically developed countries tend to offer higher salaries, likely due to greater living costs and stronger demand for specialised roles. While experience level significantly impacts earnings, with senior and executive roles receiving a much higher pay, even entry-level positions in the field are well compensated.
Skills to succeed
From the dataset, we can tell that if you wish to land a role in AI, certain skills clearly stand out. From the job postings, Python is by far the most looked for skill, appearing in over 4,400 job listings. This isn't a surprise as Python is the backbone of many machine learning, data science, and AI frameworks. Closely followed are SQL and TensorFlow, which highlight the importance of data handling and model deployment in modern AI workflows. Other in-demand skills include:
- Kubernetes: indicating a strong emphasis on containerisation and scalable deployment of ML models.
- Scala and Java: showing continued relevance in enterprise environments and big data processing.
- PyTorch: a favourite among researchers and gaining traction in production.
- Linux and Git: essential tools for development and collaboration.
- Google Cloud Platform (GCP): reflecting the shift toward cloud-based machine learning.
The graph below shows all of the skills in the dataset and how often they appear in the job postings:
However, it's important to note that while
mathematics and
statistics appear less frequently as explicity listed skills in job postings, they are often
fundamental prerequisites for many of the more popular tools and frameworks. For instance, understanding how to tune a neural network with TensorFlow or PyTorch, or how to interpret data using SQL or Python, often requires a solid grasp of statistical thinking and mathematical reasoning.
Conclusion
The 2025 AI job market is thriving, offering strong salaries, global opportunities, and a high demand for specialised skills, especially in Python, machine learning, and data engineering. While the competition is real and experience still plays a major role in salary growth, there's a clear path forward even for those just starting. Remote roles, international employment, and varied company sizes make it possible to break into the field from almost anywhere.
For developers wondering whether to shift into AI, the data speaks for itself. The industry is not only lucrative but also full of impactful work, solving real-world problems in medicine, finance, education, and more. So, whether you're a frontend dev worried about automation or a student curious about your future, one thing's clear: Now is a great time to join in. 🚀
Thanks for reading! This is my first ever blog post, so if you have any suggestions on where I could improve, that would be very much appreciated!
Code available here.